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MongoDB Meetup
- 2. Developer Advocate EMEA @MongoDB Paris @MBeugnet MaBeuLux88 maxime@mongodb.com Meetups Workshops Conferences Hackathons Webinars
- 3. 3 MongoDB’s Intelligent Operational Data Platform is the best way of making your data simple to Organize, Use, & Enrich in Real Time, Anywhere
- 4. You probably have thousands of tables
- 5. 5 Go from this…. Customer Opportunity Contact Opportunity Team Phone Phone Objects Tables Lead NameNameOpen Activities ARR Address Contact Roles SummaryCustomer Detail Activity History Object Relational Mapping Layer
- 6. 6 To this: store objects directly… Customer Customer Opportunity Opportunity Contact Contact Lead Lead Objects Database
- 7. 7 Document Model { first_name: ‘Paul’, surname: ‘Miller’, city: ‘London’, location: { type : ‘Point’, coordinates : [45.123,47.232] }, cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } ] } MongoDB RDBMS
- 8. 8 Developer Agility - Documents { first_name: ‘Paul’, surname: ‘Miller’, ID: 125678, city: ‘London’, location: { type : ‘Point’, coordinates : [45.123,47.232] }, Profession: [‘banking’, ‘finance’, ‘trader’], cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } ] } Fields can contain an array of sub-documents Typed field values Fields can contain arrays String Number Geo-Location Fields
- 9. 9 Developer Agility – Flexible Schema { product_name: ‘Acme Paint’, sku: "123-567-845", color: [‘Red’, ‘Green’], size_oz: [8, 32], finish: [‘satin’, ‘eggshell’] } { product_name: ‘T-shirt’, sku : "123-589-234", size: [‘S’, ‘M’, ‘L’, ‘XL’], color: [‘Heather Gray’ … ], material: ‘100% cotton’, wash: ‘cold’, dry: ‘tumble dry low’ } { product_name: ‘Mountain Bike’, sku : "143-534-678", brake_style: ‘mechanical disc’, color: ‘grey’, frame_material: ‘aluminum’, no_speeds: 21, package_height: ‘7.5x32.9x55’, weight_lbs: 44.05, suspension_type: ‘dual’, wheel_size_in: 26 }
- 10. 10 Developer Agility – Use Your Favourites Morphia MEAN Stack
- 11. 11 Fully Indexable Fully featured secondary indexes • Primary Index Every Collection has a primary key index • Compound Index Index against multiple keys in the document • MultiKey Index Index into arrays • Text Indexes Support for text searches • GeoSpatial Indexes 2d & 2dsphere indexes for spatial geometries • Hashed Indexes Hashed based values for sharding Index Types • TTL Indexes Single Field indexes, when expired delete the document • Unique Indexes Ensures value is not duplicated • Partial Indexes Expression based indexes, allowing indexes on subsets of data • Case Insensitive Indexes supports text search using case insensitive search • Sparse Indexes Only index documents which have the given field Index Features
- 12. 12 Aggregations Advanced data processing pipeline for transformations and analytics • Multiple stages • Similar to a unix pipe Build complex pipeline by chaining commands together • Rich Expressions Collection db.orders.aggregate( [ $match stage { $match: { status: "A" } }, $group stage { $group: { _id: "$cust_id",total: { $sum: "$amount" } } } ] ) { cust_id: "A123", amount: 500, status: "A", } { cust_id: "A123", amount: 250, status: "A", } { cust_id: "B212", amount: 200, status: "A", } { cust_id: "A123", amount: 300, status: "D", } Orders { cust_id: "A123", amount: 500, status: "A", } { cust_id: "A123", amount: 250, status: "A", } { cust_id: "B212", amount: 200, status: "A", } { id: "A123", total: 750 } { id: "B212", total: 200 } $match $group
- 13. 13 Aggregation Features A feature rich analytical framework • $match • $group • $facet • $geoNear • $graphLookup Pipeline Stages • Mathematical $add, $abs, $substract, $multiply, $divide, $log, $log10, $stdDevPop, $stdDevSam, $avg, $sqrt, $pow, $sum, $zip, $convert, etc. • Array $push, $reduce, $reverseArray, $addToSet, $arrayElemAt, $slice, etc. Operators • $lookup • $project • $sort • $unwind • $out • Conditionals $and, $or, $eq, $lt, $lte, $gt, $gte, $cmp, $cond, $switch, $in, etc • Date $dateFromParts, $dateToParts, $dateFromString, $dateToString, $dayOfMonth, $isoWeek, $minute, $month, $year, etc. • String $toUpper, $toLower, $substr, $strcasecmp, $concat, $split, etc. • Laterals $exp, $let, $literal, $map, $type, etc
- 14. 14 Compared to SQL JOINs and aggregation SELECT city, SUM(annual_spend) Total_Spend, AVG(annual_spend) Average_Spend, MAX(annual_spend) Max_Spend, COUNT(annual_spend) customers FROM ( SELECT t1.city, customer.annual_spend FROM customer LEFT JOIN ( SELECT address.address_id, city.city, address.customer_id, address.location FROM address LEFT JOIN city ON address.city_id = city.city_id ) AS t1 ON (customer.customer_id = t1.customer_id AND t1.location = "home") ) AS t2 GROUP BY city; SQL queries have a nested structure Understanding the outer layers requires understanding the inner ones So SQL has to be read “inside-out”
- 15. 15 db.customers.aggregate([ { $unwind: "$address", }, { $match: {"address.location": "home"} }, { $group: { _id: "$address.city", totalSpend: {$sum: "$annualSpend"}, averageSpend: {$avg: "$annualSpend"}, maximumSpend: {$max: "$annualSpend"}, customers: {$sum: 1} } } ]) Versatile: Complex queries fast to create, optimize, & maintain MongoDB’s aggregation framework has the flexibility you need to get value from your data, but without the complexity and fragility of SQL These “phases” are distinct and easy to understand They can be thought about in order… no nesting.
- 16. 16 Developer Agility – Compass – MongoDB GUI Debug & Optimize Visualize & Explore Insert, Modify, & Delete
- 17. 17 High Availability and Data Durability – Replica Sets SecondarySecondary Primary
- 19. 19 Replica Set Node Failure SecondarySecondary Primary No Heartbeat
- 21. 21 New Replica Set – 2 Nodes SecondaryPrimary Heartbeat And New Primary
- 22. 22 Replica Set Repair SecondaryPrimary Secondary Rejoin and resync
- 24. 24 Strong Consistency SecondarySecondary Primary Client Application Client Driver Write Read
- 25. 25 Eventual Consistency SecondarySecondary Primary Client Application Client Driver Write Read Read
- 27. 27 Replica Set Read Preference Write Concern Read Concern
- 28. #MDBlocal#MDBlocal MongoDB 3.6 adds compression of wire protocol traffic between client and database • Up to 80% bandwidth savings MongoDB End to End Compression • Wire protocol • Intra-cluster • Indexes in memory • Storage Application MongoDB Primary Replica Wire Protocol Compression MongoDB Secondary Replica Single ViewMongoDB Secondary Replica Single ViewMongoDB Secondary Replica Single ViewMongoDB Secondary Replica Single ViewMongoDB Secondary Replica MongoDB Secondary Replica Intra-Cluster Compression Compression of Data on Disk Compression of Indexes in Memory End to End Compression
- 30. #MDBlocal#MDBlocal JSON Schema Enforces strict schema structure over a complete collection for data governance & quality • Builds on document validation introduced by restricting new content that can be added to a document • Enforces presence, type, and values for document content, including nested array • Simplifies application logic Tunable: enforce document structure, log warnings, or allow complete schema flexibility Queryable: identify all existing documents that do not comply
- 31. #MDBlocal#MDBlocal JSON Schema db.createCollection( "orders", {validator: {$jsonSchema: {properties: {line_items: {type: "array", items: {properties: {title: {type: "string"}, price: {type: "number", minimum: 0.0} }, required: ["_id", "title", "price"], additionalProperties: false}}}, required: ["line_items"]}}} )
- 32. 32 Versatile: MongoDB Change Streams Enabling developers to build reactive, real-time servicesChangeStreamsAPI Business Apps User Data Sensors Clickstream Real-Time Event Notifications Message Queue
- 33. Change Streams db.coll.watch() db.coll.watch([{$match: {operationType: “insert”}}]) db.coll.watch([], {fullDocument:“updateLookup”}) db.coll.watch([], {resumeAfter:<cachedResumeToken>}) • • • • •
- 34. Change Streams => cursors cursor = db.users.watch([ ], {"fullDocument":"updateLookup"}); while ( !cursor.isExhausted() ) { if ( cursor.hasNext() ) { print(tojson(cursor.next())); } }
- 35. Characteristics of Change Streams •Resumable •Targeted Changes •Total ordering •Durability •Security •Ease of use •Idempotence
- 36. Characteristics of Retryable Writes •Automatic Drivers logic • Network errors • Elections • NOT for logic errors •Safe • For both non-idempotent and idempotent writes • NOT for multi: true
- 37. Retryable Writes => Super easy! uri = "mongodb://example.com:27017/?retryWrites=true" client = MongoClient(uri) database = client.database collection = database.collection
- 38. 38 Easy: MongoDB Multi-Document ACID Transactions Just like relational transactions • Multi-statement, familiar relational syntax • Easy to add to any application • Multiple documents in 1 or many collections and databases ACID guarantees • Snapshot isolation, all or nothing execution • No performance impact for non-transactional operations Planning • MongoDB 4.0: replica set • MongoDB 4.2: extended to sharded clusters
- 39. 39 Sophisticated Analytics & Visualizations Of Data In Place • Rich MongoDB query language & idiomatic drivers • Connector for BI • Connector for Spark • Charts (beta)
- 40. MongoDB Charts: Create, Visualize, Share Work with complex data Connect to data sources securely. Filter. Sample. Visualize. Share dashboards and collaborate
- 41. 41 Replica Set Bottlenecks Application Driver Primary /data Secondary /data Secondary /data RAM Limits on single server CPU Limits on single server Network Bandwidth Disk I/O
- 42. 42 Reasons to Shard Performance Data locality Recovery Time Objective (RTO)
- 43. Sharded Cluster Application mongos mongos mongos Driver
- 44. 44 Sharded Cluster Application mongos mongos mongos Driver Config Server
- 45. Cloud ManagerOps Manager MongoDB Atlas Private DBaaS Compatibility multi-environment Hybrid DBaaS Public DBaaS Fully managed Same codebase, same API & same UI
- 46. 46 Operational Agility – Atlas - Database as a Service Self-service, elastic, and automated Secure by defaultGlobal and highly available Continuous backups Real-time monitoring and optimization Cloud agnostic
- 47. MongoDB Stitch The Best Way to Work With Data
- 48. Focus Your Energy Where You Can Make a Difference App Backend Infrastructure Core Database Functionality Storage Service integrations, data access control Code that moves the business forward Managing OS, Scale, Security, Backups, etc. Time 40% 40% 20%
- 49. Focus Your Energy Where You Can Make a Difference App Backend Infrastructure Core Database Functionality Storage Service integrations, data access control Code that moves the business forward Managing OS, Scale, Security, Backups, etc. MongoDB Atlas Time 40% 40% 20%
- 50. Focus Your Energy Where You Can Make a Difference App Backend Infrastructure Core Database Functionality Storage Service integrations, data access control Code that moves the business forward Managing OS, Scale, Security, Backups, etc. MongoDB Atlas MongoDB Stitch Fully managed Elastic scale Highly Available Secure Time 40% 40% 20%
- 51. Focus Your Energy Where You Can Make a Difference App Backend Infrastructure Core Database Functionality Storage Service integrations, data access control Code that moves the business forward Managing OS, Scale, Security, Backups, etc. MongoDB Atlas MongoDB Stitch Fully managed Elastic scale Highly Available Secure Customer can focus here Time 40% 40% 20%
- 52. Streamlines app development with simple, secure access to data and services from the client with thousands of lines less code to write and no infrastructure to manage – getting your apps to market faster while reducing operational costs. Stitch QueryAnywhere Full power of MongoDB document model & query language in frontend code Fine-grained security policies through declarative rules MongoDB Stitch Serverless Platform Services
- 53. Streamlines app development with simple, secure access to data and services from the client with thousands of lines less code to write and no infrastructure to manage – getting your apps to market faster while reducing operational costs. Stitch QueryAnywhere Full power of MongoDB document model & query language in frontend code Fine-grained security policies through declarative rules Stitch Functions Run simple JavaScript functions in Stitch’s serverless environment Power apps with Server-side logic, or enable Data as a Service with custom APIs. MongoDB Stitch Serverless Platform Services
- 54. Streamlines app development with simple, secure access to data and services from the client with thousands of lines less code to write and no infrastructure to manage – getting your apps to market faster while reducing operational costs. Stitch QueryAnywhere Full power of MongoDB document model & query language in frontend code Fine-grained security policies through declarative rules Stitch Functions Run simple JavaScript functions in Stitch’s serverless environment Power apps with Server-side logic, or enable Data as a Service with custom APIs. Stitch Triggers Real-time notifications that launch functions in response to changes in the database Make further database changes, push data to other places, or interact with users MongoDB Stitch Serverless Platform Services
- 55. Stitch QueryAnywhere Full power of MongoDB document model & query language in frontend code Fine-grained security policies through declarative rules Stitch Functions Run simple JavaScript functions in Stitch’s serverless environment Power apps with Server-side logic, or enable Data as a Service with custom APIs. Stitch Mobile Sync Automatically synchronizes data between documents held locally in MongoDB Mobile and the backend database (coming soon) Streamlines app development with simple, secure access to data and services from the client with thousands of lines less code to write and no infrastructure to manage – getting your apps to market faster while reducing operational costs. Stitch Triggers Real-time notifications that launch functions in response to changes in the database Make further database changes, push data to other places, or interact with users MongoDB Stitch Serverless Platform Services
- 56. 56 Demo!